状态方程x'=[0,1,0;0,0,1;-209.827,-161.235,-23.602]x+[0,0,1]n0. 输出方程n=[208.5,133.439,0]. 用MATLAB四阶龙格库塔法求解不同步长时图像
% Define the system matrices
A = [0, 1, 0; 0, 0, 1; -209.827, -161.235, -23.602];
B = [0; 0; 1];
C = [208.5, 133.439, 0];
D = 0;
% Define the initial conditions
x0 = [0; 0; 0];
% Define the simulation time and step size
t_start = 0;
t_end = 10;
dt_vec = [0.001, 0.01, 0.1];
% Perform simulations with different step sizes
for i = 1:length(dt_vec)
dt = dt_vec(i);
t = t_start:dt:t_end;
num_steps = length(t);
% Pre-allocate memory for the output
y = zeros(num_steps, size(C, 1));
% Initialize the state vector
x = x0;
% Perform the simulation
for j = 1:num_steps
% Record the output
y(j, :) = C * x;
% Compute the k values
k1 = A * x + B * randn;
k2 = A * (x + 0.5 * dt * k1) + B * randn;
k3 = A * (x + 0.5 * dt * k2) + B * randn;
k4 = A * (x + dt * k3) + B * randn;
% Update the state vector
x = x + (dt / 6) * (k1 + 2 * k2 + 2 * k3 + k4);
end
% Plot the output
figure;
plot(t, y);
xlabel('Time (s)');
ylabel('Output');
title(sprintf('Output with dt = %g', dt));
legend('y_1', 'y_2', 'y_3');
end
```这个代码会求解状态方程的数值解,并且根据不同的步长绘制输出的图像。这里使用的是四阶龙格库塔法,它可以提供比较准确的结果。在这个例子中,我们采用了三个不同的步长(0.001,0.01和0.1),以便比较它们之间的差异
可以,直接用sym进行解方程。